Although epigenetic components play a major role in driving tumor progression in many human cancers, the methylation landscape in cancer epigenomes is still largely unexplored. Systematic sequence-based methylation analyses are notably absent and as a result, the potential clinical value of specific methylation differences and their biological impacts in cancers remain largely untapped. By identifying the aberrant methylation "hot spots" in the cancer epigenome, we can target these genes for therapeutic intervention and develop them into DNA methylation biomarkers for early detection, diagnosis, prognosis, and monitoring the response to therapy. However, to fully understand the interactions between methylation and clinical behaviors, new methods are needed to determine single-base-level specific methylation patterns across the genome. As an important clinical model for our work, we will examine subsets of chronic lymphocytic leukemia (CLL) to discover DNA methylation alterations that distinguish the sub-types of CLL and suggest underlying mechanisms for differential clinical behaviors and tumor progression. Successful completion of this study will substantially influence the clinical management of CLL patients and allow "up-front" administration of epigenetic therapies. To accomplish this, we will develop a high-throughput, large-scale, sequencing-based approach to provide efficient methods for deeply exploring the CLL methylome. In our preliminary study, we demonstrated that bisulfite sequencing can be carried out using an innovative massively parallel sequencing system (454-sequencing) that is capable of analyzing millions of DNA bases in a single run. This new generation of bisulfite sequencing will provide highly quantitative single methyl-cytosine resolution for specific methylation mapping in multiple CpG islands (CGIs). In this R33 application, we propose to optimize and develop a prototype high-throughput bisulfite sequencing method for ultra-deep analyses of DNA methylation patterns in primary CLL samples from CD38+ and CD38- CLL B-cells and test the hypothesis that the clinical behavior of subclasses of CLL can be defined in part by their distinct DNA methylation profiles that in turn affect multiple genes and signaling pathways. Specifically, we will: (1) develop a multiplexed amplicon preparation method for high-throughput, ultra-deep bisulfite sequencing;(2) develop a genome-scale approach for bisulfite sequencing of methylation-enriched genomic DNA libraries;(3) apply the innovative high-throughput bisulfite sequencing method to investigation of the CLL methylome. We believe that the technology developed will revolutionize the current analytical methods of DNA methylation, provide digital profiles of aberrant DNA methylation for individual human diseases and offer a deep-sequencing, robust method for epigenetic classification of disease subtypes.